
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "17"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 80 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 76 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	digital_ok	0.00%	0.00%	0.00%	0.00%	1.08%	0.00%	0.800096	-0.109675	-0.267532	0.417195	-1.112345	-0.673282	0.265094	0.473339	0.7315	0.7234	0.2359	3.447220	3.319505
2459593	digital_ok	0.00%	0.00%	0.00%	0.00%	2.15%	2.15%	0.303978	0.421876	-0.272386	0.521917	-0.302168	-0.147533	0.897075	0.150595	0.6582	0.6443	0.2025	2.651242	2.459864
2459592	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	0.240991	-0.755102	-0.051394	-0.557854	0.889589	-0.613025	1.928056	-0.002213	0.0289	0.0295	0.0004	nan	nan
2459591	digital_ok	0.00%	0.00%	0.00%	0.00%	1.62%	14.59%	0.873659	0.613138	-0.108965	0.001047	0.773172	-0.320043	0.991096	-0.424698	0.5360	0.5499	0.2999	2.100561	2.003716
2459590	digital_ok	0.00%	0.00%	0.00%	0.00%	1.62%	0.00%	0.651164	0.693991	-0.446972	0.173212	0.401606	-0.346024	0.773260	-0.273668	0.5406	0.5496	0.2957	2.022741	1.854888
2459589	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	0.150221	0.399166	-0.633404	-0.036107	0.798414	-0.035481	0.446167	0.050838	0.6196	0.6078	0.2312	1.950422	1.880690
2459588	digital_ok	0.00%	0.00%	0.00%	0.00%	2.69%	0.00%	0.574826	0.725330	-0.363050	0.009421	-0.290193	0.729190	0.858088	0.768532	0.7264	0.6976	0.1928	3.900116	3.218194
2459587	digital_ok	0.00%	-	-	-	3.50%	0.70%	0.677162	0.834220	0.836212	0.501041	-0.492927	-0.873167	0.235998	-0.199763	nan	nan	nan	1.183774	1.173466
2459586	digital_ok	0.00%	0.00%	0.00%	0.00%	2.16%	3.24%	-0.424341	-0.725196	-0.491353	-0.834017	-0.279557	-0.166590	0.935710	-0.057913	0.5440	0.5567	0.2874	1.979612	1.837169
2459585	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.299097	-1.053766	0.558304	-0.971645	1.829030	-0.686374	2.209018	0.511458	0.0303	0.0311	0.0005	0.000000	0.000000
2459584	digital_ok	100.00%	28.21%	25.81%	0.00%	100.00%	0.00%	1.051952	1.119942	-0.702568	-0.823290	1.521110	0.365305	8.353336	6.914101	0.4821	0.4927	0.2920	10.429561	8.043527
2459583	digital_ok	0.00%	0.00%	0.00%	0.00%	5.91%	0.00%	-0.046409	0.318033	0.202489	0.076335	-0.778587	-0.518318	1.342558	0.081090	0.5284	0.5362	0.3116	1.644547	1.618059
2459582	digital_ok	0.00%	1.62%	2.70%	0.00%	8.65%	0.00%	0.118787	-0.002894	-0.018478	0.159948	-0.376814	-0.006147	1.086648	0.077825	0.5231	0.5326	0.3187	1.799986	1.675673
2459581	digital_ok	0.00%	0.00%	1.08%	0.00%	4.32%	0.54%	0.254285	0.484287	0.167034	-0.323195	-0.706630	-0.455614	-0.001004	-0.106649	0.5349	0.5430	0.3180	1.843374	1.716514
2459580	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	0.212828	0.105222	-0.270352	-0.184540	-0.387687	-0.614065	3.073361	0.548777	0.5455	0.5579	0.3116	2.021688	1.811085
2459579	digital_ok	0.00%	0.00%	0.00%	0.00%	3.76%	0.00%	-0.004664	0.205605	0.057954	0.363477	-0.584635	-0.401218	2.269667	1.462717	0.5428	0.5556	0.3140	1.876949	1.746815
2459578	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.635816	0.029142	-0.548690	-0.699997	2.999760	1.546354	1.242732	0.160285	0.0309	0.0312	0.0007	nan	nan
2459577	digital_ok	0.00%	0.00%	0.00%	0.00%	3.78%	0.54%	0.571290	0.712497	-0.049098	-0.228895	0.462150	-0.015211	1.285798	0.547202	0.5467	0.5591	0.3100	1.928636	1.798660
2459576	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459575	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.384373	0.790823	-0.082879	-0.009056	0.042017	-0.515789	0.086600	0.195153	0.0552	0.0535	0.0048	0.000000	0.000000
2459574	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.406705	0.771065	-0.075263	0.012761	-0.107448	-0.274561	1.723693	0.915303	0.0758	0.0792	0.0113	1.167684	1.165229
2459573	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.315563	0.372681	0.291019	0.019669	0.109140	-0.636658	2.767169	2.011800	0.0767	0.0798	0.0148	0.000000	0.000000
2459572	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.050826	0.169626	0.048121	0.074826	-0.510573	-0.277376	0.176571	0.057188	0.0567	0.0533	0.0045	1.106267	1.107858
2459571	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.357070	0.042512	-0.780198	-0.753349	0.091347	0.144971	1.091525	0.040984	0.0295	0.0305	0.0008	nan	nan
2459570	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.669609	-1.174368	-0.715806	-1.508877	-0.461536	-1.052548	0.942409	0.027856	0.0572	0.0541	0.0070	0.000000	0.000000
2459569	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.476518	0.263440	0.135368	-0.000509	-0.315543	-0.261160	0.345857	-0.003594	0.0773	0.0768	0.0066	1.188246	1.189184
2459566	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.364323	0.320351	0.332800	0.086129	-0.299355	-0.276866	2.986648	1.873171	0.0737	0.0789	0.0135	0.821016	0.817974
2459565	digital_ok	0.00%	-	-	-	73.33%	0.00%	0.070714	0.070714	0.026519	0.026519	0.526814	0.526814	0.051858	0.051858	nan	nan	nan	0.000000	0.000000
2459564	digital_ok	0.00%	0.00%	0.00%	0.00%	5.20%	0.00%	-0.517351	0.547691	0.315080	0.273043	0.228382	-0.039013	1.667460	1.579588	0.7035	0.7077	0.3902	1.898102	1.690940
2459563	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459562	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459561	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459560	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459559	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	-0.467249	0.268587	0.255313	-0.017453	0.754314	0.455556	0.422233	0.005114	0.6974	0.7060	0.3808	1.784081	1.578151
2459558	digital_ok	0.00%	0.00%	0.00%	0.00%	13.98%	0.00%	-0.257812	0.250201	-0.141861	-0.066929	0.280599	-0.079736	1.466462	0.850604	0.6995	0.7027	0.3874	1.644192	1.538312
2459557	digital_ok	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0295	0.0310	0.0005	nan	nan
2459556	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	-0.322446	0.357859	0.108227	0.168848	0.120600	-0.700522	0.257158	0.374887	0.7019	0.7069	0.3848	1.651716	1.603605
2459554	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.6936	0.6958	0.4076	nan	nan
2459553	digital_ok	-	0.00%	0.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.7015	0.7040	0.3934	nan	nan
2459552	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	1.221994	4.189992	-0.020135	-0.256521	5.318389	13.619786	-0.163786	-0.218816	0.7039	0.7013	0.3857	0.000000	0.000000
2459551	digital_ok	0.00%	0.00%	0.00%	0.00%	5.38%	0.00%	0.218232	0.122853	0.196505	-0.066972	0.310600	0.337315	1.039133	1.241210	0.6934	0.7013	0.3849	1.882656	1.642792
2459550	digital_ok	-	99.18%	99.18%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0310	0.0305	0.0003	nan	nan
2459549	digital_ok	0.00%	0.00%	0.00%	0.00%	4.86%	0.00%	1.409113	0.192999	0.008345	-0.493757	-0.494886	-0.713984	0.980218	1.309965	0.6933	0.7013	0.3964	1.953424	1.719195
2459542	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	6.791527	0.558994	1.223028	-0.285790	-0.634988	-0.670209	0.710388	0.033869	0.7421	0.7504	0.3476	3.847561	3.400409
2459541	digital_ok	100.00%	1.34%	1.34%	0.00%	100.00%	0.00%	5.780286	0.863172	-0.409045	-0.614021	-0.251497	0.815907	-0.006085	-0.078816	0.7386	0.7411	0.3201	5.791330	5.078246
2459540	digital_ok	0.00%	0.00%	0.00%	0.00%	22.32%	0.00%	-0.433160	0.635075	0.197468	0.015853	0.160376	-0.556205	0.548954	0.321109	0.7476	0.7357	0.3545	1.495633	1.426810
2459536	digital_ok	0.00%	0.00%	0.00%	0.00%	5.93%	0.00%	0.024956	0.661619	0.507385	-0.714768	0.700311	0.456929	-0.425834	-1.180154	0.7307	0.7342	0.4134	2.046609	1.773187
2459535	digital_ok	0.00%	0.00%	0.00%	0.00%	21.43%	0.00%	-0.358278	0.237408	0.401237	0.015518	-0.209668	-0.528354	1.587530	0.817868	0.7766	0.7566	0.3642	1.872809	1.630589
2459534	digital_ok	0.00%	0.00%	0.00%	0.00%	21.43%	0.00%	-0.439355	0.185406	0.488021	-0.035829	0.089040	-0.816682	2.563835	1.229115	0.7713	0.7575	0.3533	1.785189	1.634198
2459533	digital_ok	0.00%	0.00%	0.00%	0.00%	4.89%	3.26%	0.068436	0.682455	0.116710	-0.571523	1.051413	-0.625710	2.780759	0.996423	0.7166	0.7147	0.4020	1.886377	1.617776
2459532	digital_ok	0.00%	0.00%	0.00%	0.00%	5.00%	1.67%	-0.238558	0.621998	0.364532	-0.065755	0.539116	-0.970650	1.187403	0.047473	0.7174	0.7117	0.4039	1.934825	1.672022
2459530	digital_ok	0.00%	0.00%	0.00%	0.00%	4.73%	0.00%	-0.461395	0.448056	0.262666	0.012336	0.691970	0.450436	0.965221	0.666445	0.7375	0.7300	0.3984	1.902674	1.718662
2459527	digital_ok	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	digital_ok	0.00%	0.00%	0.00%	0.00%	100.00%	0.00%	-0.114615	0.052856	0.737493	-0.304817	0.868768	-0.066869	1.230329	0.231343	0.8945	0.9258	0.3290	0.000000	0.000000
2459523	digital_ok	0.00%	-	-	-	22.45%	2.04%	0.210146	0.991247	0.528402	-0.482698	-0.065192	-0.649870	1.738096	0.935954	nan	nan	nan	2.800819	2.117070
2459522	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.225819	1.538368	-0.063772	-0.213349	-0.322085	4.193943	3.366201	3.022861	0.6806	0.6331	0.3781	5.833470	6.469766
2459513	digital_ok	0.00%	100.00%	100.00%	0.00%	-	-	-0.254281	0.142931	-0.522666	-0.723976	0.809347	1.482388	-0.379956	-0.099489	0.0310	0.0350	0.0006	nan	nan
2459508	digital_ok	0.00%	0.00%	0.00%	0.00%	81.58%	0.00%	-0.631367	-0.359431	0.509666	-0.217544	-0.178556	-0.472475	0.670200	-0.423592	0.8993	0.9259	0.2099	0.000000	0.000000
2459505	digital_ok	0.00%	0.00%	0.00%	0.00%	0.00%	0.00%	-0.363106	0.447693	-0.260551	0.032342	0.989613	0.028622	0.925434	0.384637	0.8892	0.8537	0.1987	5.476119	3.823374
2459503	digital_ok	100.00%	0.00%	0.00%	0.00%	100.00%	0.00%	0.063599	-0.108376	0.144201	-0.332564	-0.358505	-0.017830	5.897933	1.975658	0.8454	0.8354	0.4892	0.000000	0.000000
2459501	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	1.356223	0.360763	-0.806964	-0.760178	1.545142	-0.789065	15.677505	4.405592	0.1093	0.0956	0.0118	0.000000	0.000000
2459500	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	-0.190633	-0.088834	0.047460	-0.861066	0.252826	-0.913241	1.045847	0.097187	0.0956	0.0996	0.0100	0.000000	0.000000
2459499	digital_ok	0.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.136621	-0.055086	0.558005	-0.522803	0.617845	-0.790797	3.100664	0.903593	0.0764	0.1070	0.0059	0.000000	0.000000
2459498	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	6.450208	0.175750	1.625179	-0.794814	7.166414	-0.769544	36.925502	2.633739	0.0583	0.0889	0.0099	0.000000	0.000000
2459497	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.689838	0.358742	-0.080815	-0.804604	-0.691004	-0.973824	7.665448	2.958385	0.0952	0.0898	0.0122	0.000000	0.000000
2459496	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.962984	0.320284	0.715228	-0.440918	0.083722	-1.021859	7.178628	1.916696	0.1116	0.1142	0.0156	0.000000	0.000000
2459495	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.202888	0.188195	0.671364	-0.522759	0.045094	-0.868899	7.846367	3.638013	0.0997	0.0966	0.0131	0.000000	0.000000
2459494	digital_ok	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	0.413903	0.151708	0.794461	-0.427229	0.349302	-0.961015	12.928318	5.333709	0.1045	0.1074	0.0143	0.000000	0.000000
2459492	digital_ok	0.00%	0.00%	0.00%	0.00%	50.00%	0.00%	0.486633	1.697221	-1.343002	-1.458597	-0.059178	-0.160993	1.721006	3.197599	0.7521	0.7992	0.3400	0.400981	0.330588
2459491	digital_ok	0.00%	0.00%	0.00%	0.00%	50.00%	0.00%	0.584939	1.056650	-1.306406	-1.387168	0.084777	-0.439669	-0.382643	-0.538896	0.7972	0.8162	0.2632	0.998837	0.863418
2459490	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	0.244415	1.512015	-1.892379	-1.823899	0.248056	-0.311878	-0.785117	-0.293066	0.7402	0.7943	0.3752	2.123531	1.955276
2459489	digital_ok	0.00%	0.00%	0.00%	0.00%	47.37%	0.00%	0.535450	1.595246	-1.448303	-1.540173	0.054387	-0.118773	-0.411304	-0.387537	0.7640	0.8043	0.3108	2.116398	1.819935
2459488	digital_ok	0.00%	0.00%	0.00%	0.00%	85.71%	0.00%	0.644619	1.510703	-0.817191	-1.136898	-0.090609	0.041255	-0.220509	-0.536907	0.7648	0.8063	0.3568	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 17 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 17, Node 1:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 17: 2459603

Antenna 17: 2459602

Antenna 17: 2459598

Antenna 17: 2459597

Antenna 17: 2459596

Antenna 17: 2459595

Antenna 17: 2459594

Antenna 17: 2459593

Antenna 17: 2459592

Antenna 17: 2459591

Antenna 17: 2459590

Antenna 17: 2459589

Antenna 17: 2459588

Antenna 17: 2459587

Antenna 17: 2459586

Antenna 17: 2459585

Antenna 17: 2459584

Antenna 17: 2459583

Antenna 17: 2459582

Antenna 17: 2459581

Antenna 17: 2459580

Antenna 17: 2459579

Antenna 17: 2459578

Antenna 17: 2459577

Antenna 17: 2459576

Antenna 17: 2459575

Antenna 17: 2459574

Antenna 17: 2459573

Antenna 17: 2459572

Antenna 17: 2459571

Antenna 17: 2459570

Antenna 17: 2459569

Antenna 17: 2459566

Antenna 17: 2459565

Antenna 17: 2459564

Antenna 17: 2459563

Antenna 17: 2459562

Antenna 17: 2459561

Antenna 17: 2459560

Antenna 17: 2459559

Antenna 17: 2459558

Antenna 17: 2459556

Antenna 17: 2459552

Antenna 17: 2459551

Antenna 17: 2459549

Antenna 17: 2459542

Antenna 17: 2459541

Antenna 17: 2459540

Antenna 17: 2459536

Antenna 17: 2459535

Antenna 17: 2459534

Antenna 17: 2459533

Antenna 17: 2459532

Antenna 17: 2459530

Antenna 17: 2459527

Antenna 17: 2459524

Antenna 17: 2459523

Antenna 17: 2459522

Antenna 17: 2459513

Antenna 17: 2459508

Antenna 17: 2459506

Antenna 17: 2459505

Antenna 17: 2459503

Antenna 17: 2459501

Antenna 17: 2459500

Antenna 17: 2459499

Antenna 17: 2459498

Antenna 17: 2459497

Antenna 17: 2459496

Antenna 17: 2459495

Antenna 17: 2459494

Antenna 17: 2459492

Antenna 17: 2459491

Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶